Quick Demo

Sachin Yadav , IIT Gandhinagar, sachin.yadav@iitgn.ac.in

from IPython.display import HTML
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IRIS Flower data set

The data set contains information about three species of IRIS flowers namely:

• Iris setosa
• Iris versicolor
• Iris virginica

Four features are collected from each sample, sepal-length, sepal-width, petal-length and petal-width in centi-meters.

# Common imports
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

import plotly.express as px

iris_df = pd.read_csv("./data/IRIS.csv.gz", compression="gzip")
iris_df.sample(5)

	Unnamed: 0	sepal_length	sepal_width	petal_length	petal_width	species
148	148	6.2	3.4	5.4	2.3	Iris-virginica
118	118	7.7	2.6	6.9	2.3	Iris-virginica
28	28	5.2	3.4	1.4	0.2	Iris-setosa
79	79	5.7	2.6	3.5	1.0	Iris-versicolor
135	135	7.7	3.0	6.1	2.3	Iris-virginica

fig = px.scatter_3d(iris_df, x='sepal_length', y='sepal_width', z='petal_width',
              color='species', template="plotly_dark")
fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
fig.show()

COVID-19 Dataset

covid_df = pd.read_csv("./data/owid-covid-data.csv.gz", compression="gzip")
covid_df.sample(5)

	Unnamed: 0	iso_code	continent	location	date	total_cases	new_cases	new_cases_smoothed	total_deaths	new_deaths	...	female_smokers	male_smokers	handwashing_facilities	hospital_beds_per_thousand	life_expectancy	human_development_index	excess_mortality_cumulative_absolute	excess_mortality_cumulative	excess_mortality	excess_mortality_cumulative_per_million
88604	88604	OWID_LIC	NaN	Low income	2020-04-18	4207.0	277.0	211.429	164.0	10.0	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
113927	113927	OWID_OCE	NaN	Oceania	2020-08-14	25132.0	327.0	367.857	405.0	4.0	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
56866	56866	GEO	Asia	Georgia	2020-08-13	1283.0	5.0	11.000	17.0	0.0	...	5.3	55.5	NaN	2.6	73.77	0.812	NaN	NaN	NaN	NaN
150248	150248	TGO	Africa	Togo	2021-11-20	26199.0	0.0	7.286	243.0	0.0	...	0.9	14.2	10.475	0.7	61.04	0.515	NaN	NaN	NaN	NaN
43528	43528	ECU	South America	Ecuador	2020-06-16	47943.0	621.0	575.143	3970.0	41.0	...	2.0	12.3	80.635	1.5	77.01	0.759	NaN	NaN	NaN	NaN

5 rows × 68 columns

required_columns = ["iso_code", "location", "continent", "date", "new_cases_smoothed", "total_cases"]
covid_df = covid_df.dropna(subset = required_columns)

covid_df = covid_df.sort_values("date")

covid_df[['iso_code', 'location']].sample(8)

	iso_code	location
40387	COD	Democratic Republic of Congo
148642	THA	Thailand
73189	IRQ	Iraq
109618	NER	Niger
3082	AND	Andorra
25062	BDI	Burundi
117543	PAN	Panama
126394	LCA	Saint Lucia

Covid-19 New Cases Worldwide on 23 December 2021

covid_day_df = covid_df[covid_df.date == "2021-12-23"]
covid_day_df.sample(5)

	Unnamed: 0	iso_code	continent	location	date	total_cases	new_cases	new_cases_smoothed	total_deaths	new_deaths	...	female_smokers	male_smokers	handwashing_facilities	hospital_beds_per_thousand	life_expectancy	human_development_index	excess_mortality_cumulative_absolute	excess_mortality_cumulative	excess_mortality	excess_mortality_cumulative_per_million
126973	126973	LCA	North America	Saint Lucia	2021-12-23	13225.0	16.0	14.000	295.0	0.0	...	NaN	NaN	87.202	1.30	76.20	0.759	NaN	NaN	NaN	NaN
21208	21208	BWA	Africa	Botswana	2021-12-23	208994.0	4293.0	1304.286	2427.0	2.0	...	5.7	34.4	NaN	1.80	69.59	0.735	NaN	NaN	NaN	NaN
117553	117553	PAN	North America	Panama	2021-12-23	485512.0	719.0	526.857	7406.0	1.0	...	2.4	9.9	NaN	2.30	78.51	0.815	NaN	NaN	NaN	NaN
84158	84158	LVA	Europe	Latvia	2021-12-23	270158.0	954.0	741.857	4489.0	12.0	...	25.6	51.0	NaN	5.57	75.29	0.866	NaN	NaN	NaN	NaN
93696	93696	MYS	Asia	Malaysia	2021-12-23	2731713.0	3510.0	3473.000	31265.0	44.0	...	1.0	42.4	NaN	1.90	76.16	0.810	NaN	NaN	NaN	NaN

5 rows × 68 columns

fig = px.scatter_geo(covid_day_df, locations="iso_code", color="continent",
                     hover_name="location", size="new_cases_smoothed",
                     projection="natural earth", template="plotly_dark")

fig.show()

Covid-19 Total Cases over the days

fig = px.scatter_geo(covid_df, locations="iso_code", color="continent",
                     hover_name="location", size="total_cases",
                     projection="natural earth", animation_frame="date", template="plotly_dark")

fig.show()

MNIST Dataset

import torchvision
import os

import matplotlib.pyplot as plt
from matplotlib import rc
from matplotlib.animation import FuncAnimation
from matplotlib import animation

rc('animation', html='jshtml')

frn = 10 # Number of frames to process in the animation
fps = 0.5 # Frames per second
mywriter = animation.PillowWriter(fps=fps) 

mnist_dataset = torchvision.datasets.MNIST(root = "data/mnist", train = True, download = True, transform=torchvision.transforms.ToTensor())

fig, ax = plt.subplots(figsize = (10, 10))

def change_plot(frame_idx):
    ax.cla()
    image_tensor = mnist_dataset[frame_idx][0]
    image_tensor_gray = image_tensor[0]
    image_tensor_gray = image_tensor_gray * 255
    ax.matshow(image_tensor_gray, cmap = "gray")
    for i in range(image_tensor_gray.shape[0]):
        for j in range(image_tensor_gray.shape[1]):
            ax.text(i, j, str(int(image_tensor_gray[j][i].item())), va = "center", ha = "center", color = "blue", fontsize = "small")
    ax.axis("off")
    plt.tight_layout()

anim = FuncAnimation(fig, change_plot, frn, interval=1000 / fps)
plt.close()
anim

Once Loop Reflect

<Figure size 432x288 with 0 Axes>

mywriter = animation.PillowWriter(fps=fps)

if not os.path.exists("./assets/gif"):
    os.makedir("./assets/gif")
    
anim.save('./assets/gif/mnist.gif',writer=mywriter)

<Figure size 432x288 with 0 Axes>

Linear Regression with and without L2 regularisation

Credits: The below Hugging Face Space Demo was created by Prof. Nipun Batra for ES 654 2022 course. We have only embedded it in our notebook to demonstrate utility to allow user to run a model or interact with sliders, etc. in the notebook View original at: https://huggingface.co/spaces/Nipun/RidgeDemo

from IPython.display import HTML

HTML("""
<iframe src="https://hf.space/streamlit/Nipun/RidgeDemo/+" data-src="https://hf.space/streamlit/Nipun/RidgeDemo/+" data-sdk="streamlit" title="Streamlit app" height="800px" width="100%"></iframe>
""")